MetPy: A Meteorological Python Library for Data Analysis and Visualization
MetPy: A Meteorological Python Library for Data Analysis and Visualization
复制标题
MetPy：用于数据分析和可视化的气象 Python 库
DOI：
10.1175/bams-d-21-0125.1
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发表时间：
2022
影响因子：
8
通讯作者：
Marsh, Patrick T.
中科院分区：
文献类型：
--
作者：
May, Ryan M.;Goebbert, Kevin H.;Thielen, Jonathan E.;Leeman, John R.;Camron, M. Drew;Bruick, Zachary;Bruning, Eric C.;Manser, Russell P.;Arms, Sean C.;Marsh, Patrick T.
MetPy 是一个基于 Python 的开源气象学软件包，提供广泛构建在强大的科学 Python 软件堆栈之上的特定领域的功能，其中包括 NumPy、SciPy、Matplotlib 和 xarray 等库。该项目的目标是将 GEMPAK（和类似软件工具）的天气分析功能引入现代计算范例。 MetPy 努力在其开发中采用最佳实践，包括软件测试、持续集成和基于 Web 的文档的自动发布。因此，MetPy 代表了一个可持续的长期项目，可以满足气象界的需求。 MetPy 的开发在很大程度上是由其用户社区推动的，既通过 Stack Overflow 等各种开放公共论坛的反馈，也通过 GitHub 协作软件开发平台促进的代码贡献。 MetPy 最近发布了 1.0 版本，具有用于分析和可视化气象数据集的强大功能。虽然 MetPy 的早期版本已经得到广泛使用，但 1.0 版本在完整性和对编程接口长期支持的承诺方面代表了一个重要的里程碑。本文概述了 MetPy 的功能套件，包括使用标记数组和物理单位信息作为其核心数据模型、单位感知计算、横截面、类似 skewT 和 GEMPAK 的绘图、站模型图以及对解析各种气象数据格式的支持。还讨论了 MetPy 未来计划开发的总体路线图。
MetPy is an open-source, Python-based package for meteorology, providing domain-specific functionality built extensively on top of the robust scientific Python software stack, which includes libraries like NumPy, SciPy, Matplotlib, and xarray. The goal of the project is to bring the weather analysis capabilities of GEMPAK (and similar software tools) into a modern computing paradigm. MetPy strives to employ best practices in its development, including software tests, continuous integration, and automated publishing of web-based documentation. As such, MetPy represents a sustainable, long-term project that fills a need for the meteorological community. MetPy’s development is substantially driven by its user community, both through feedback on a variety of open, public forums like Stack Overflow, and through code contributions facilitated by the GitHub collaborative software development platform. MetPy has recently seen the release of version 1.0, with robust functionality for analyzing and visualizing meteorological datasets. While previous versions of MetPy have already seen extensive use, the 1.0 release represents a significant milestone in terms of completeness and a commitment to long-term support for the programming interfaces. This article provides an overview of MetPy’s suite of capabilities, including its use of labeled arrays and physical unit information as its core data model, unit-aware calculations, cross sections, skewTand GEMPAK-like plotting, station model plots, and support for parsing a variety of meteorological data formats. The general road map for future planned development for MetPy is also discussed.